Systems and methods for using trained predictive modeling to reduce misdiagnoses of critical illnesses

Abstract

A trained predictive server is provided for determining that a diagnosis and treatment plan is inaccurate. The trained predictive server includes a processor configured to receive a set of prior authorization (PA) data associated with a medical claim for a patient, and determine that the set of PA data indicates that the medical claim is associated with a qualifying critical illness. The processor is further configured to extract component data from the set of PA data, and apply the extracted component data to a trained predictive model associated with the qualifying critical illness to determine whether the medical claim is associated with an inaccurate diagnosis and treatment plan. Upon determining that the medical claim is associated with an inaccurate diagnosis and treatment plan, the processor is configured to generate a request for a consulting review of the diagnosis and treatment plan using the set of PA data.

What is claimed is: 
     
         1 . A trained predictive server for determining that a diagnosis and treatment plan is inaccurate, the trained predictive server comprising a processor and a memory, said processor configured to:
 receive a set of prior authorization (PA) data associated with a medical claim for a patient;   determine that the set of PA data indicates that the medical claim is associated with a qualifying critical illness;   extract component data from the set of PA data;   apply the extracted component data to a trained predictive model associated with the qualifying critical illness to determine whether the medical claim is associated with an inaccurate diagnosis and treatment plan; and   upon determining that the medical claim is associated with the inaccurate diagnosis and treatment plan, generate a request for a consulting review of the diagnosis and treatment plan using the set of PA data.   
     
     
         2 . The trained predictive server of  claim 1 , wherein the processor is further configured to:
 identify a list of qualifying critical illnesses from a storage device in communication with the trained predictive server; and   apply the list to the set of PA data to determine that the set of PA data indicates that the medical claim is associated with the qualifying critical illness.   
     
     
         3 . The trained predictive server of  claim 1 , wherein the processor is further configured to:
 identify a list of features for extraction; and   extract the component data, based on the list of features, from the set of PA data.   
     
     
         4 . The trained predictive server of  claim 1 , wherein the processor is further configured to:
 identify a consulting review provider based on the set of PA data; and   transmit the request for the consulting review of the diagnosis and treatment plan to a computing device associated with the consulting review provider.   
     
     
         5 . The trained predictive server of  claim 1 , wherein the processor is further configured to:
 determine a likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan;   compare the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan against a predetermined threshold to evaluate inaccuracies in the diagnosis and treatment plan; and   on condition that the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan is greater than the predetermined threshold, determine that the medical claim is associated with the inaccurate diagnosis and treatment plan.   
     
     
         6 . The trained predictive server of  claim 1 , wherein the processor is further configured to:
 determine a likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan;   compare the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan against a predetermined threshold to evaluate inaccuracies in the diagnosis and treatment plan; and   on condition that the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan is less than the predetermined threshold, generate a request that the medical claim be processed.   
     
     
         7 . The trained predictive server of  claim 1 , wherein the processor is further configured to:
 determine a likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan;   compare the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan against a plurality of predetermined thresholds to evaluate inaccuracies in the diagnosis and treatment plan, the plurality of predetermined thresholds including an upper predetermined threshold and a lower predetermined threshold; and   on condition that the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan is between the upper predetermined threshold and the lower predetermined threshold, transmit an alert to a secondary device to request input regarding whether the consulting review is needed.   
     
     
         8 . A method for determining that a diagnosis and treatment plan is inaccurate and performed by a trained predictive server including a processor and a memory, the method comprising:
 receiving a set of prior authorization (PA) data associated with a medical claim for a patient;   determining that the set of PA data indicates that the medical claim is associated with a qualifying critical illness;   extracting component data from the set of PA data;   applying the extracted component data to a trained predictive model associated with the qualifying critical illness to determine whether the medical claim is associated with an inaccurate diagnosis and treatment plan; and   upon determining that the medical claim is associated with the inaccurate diagnosis and treatment plan, generating a request for a consulting review of the diagnosis and treatment plan using the set of PA data.   
     
     
         9 . The method of  claim 8 , further comprising identifying a list of qualifying critical illnesses from a storage device in communication with the trained predictive server, wherein the list of qualifying critical illnesses is applied to determine whether the set of PA data indicates that the medical claim is associated with the qualifying critical illness. 
     
     
         10 . The method of  claim 8 , further comprising identifying a list of features for extraction, wherein the list of features for extraction is used to extract the component data from the set of PA data. 
     
     
         11 . The method of  claim 8 , further comprising:
 identifying a consulting review provider based on the set of PA data; and   transmitting the request for the consulting review of the diagnosis and treatment plan to a computing device associated with the consulting review provider.   
     
     
         12 . The method of  claim 8 , further comprising:
 determining a likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan;   comparing the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan against a predetermined threshold to evaluate inaccuracies in the diagnosis and treatment plan; and   on condition that the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan is greater than the predetermined threshold, determining that the medical claim is associated with the inaccurate diagnosis and treatment plan.   
     
     
         13 . The method of  claim 8 , further comprising:
 determining a likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan;   comparing the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan against a predetermined threshold to evaluate inaccuracies in the diagnosis and treatment plan; and   on condition that the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan is less than the predetermined threshold, generating a request that the medical claim be processed.   
     
     
         14 . The method of  claim 8 , further comprising:
 determining a likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan;   comparing the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan against a plurality of predetermined thresholds to evaluate inaccuracies in the diagnosis and treatment plan, the plurality of predetermined thresholds including an upper predetermined threshold and a lower predetermined threshold; and   on condition that the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan is between the upper predetermined threshold and the lower predetermined threshold, transmitting an alert to a secondary device to request input regarding whether the consulting review is needed.   
     
     
         15 . A trained predictive system for determining that a diagnosis and treatment plan is inaccurate, said trained predictive system comprising:
 a first claim database server comprising a database processor and a database memory, the database memory includes a set of prior authorization (PA) data associated with a medical claim for a patient, the database processor configured to determine that the set of PA data indicates that the medical claim is associated with a qualifying critical illness; and   a trained predictive server in communication with the first claim database server, the trained predictive server comprising a processor and a memory, the processor configured to:
 receive the set of PA data associated with the medical claim for the patient from the first claim database server; 
 extract component data from the set of PA data; and 
 apply the extracted component data to a trained predictive model associated with the qualifying critical illness to determine whether the medical claim is associated with an inaccurate diagnosis and treatment plan; and 
   
       wherein the database processor is further configured to:
 receive an indication that the medical claim is associated with the inaccurate diagnosis and treatment plan from the trained predictive server; and 
 generate a request for a consulting review of the diagnosis and treatment plan using the set of PA data. 
 
     
     
         16 . The trained predictive system of  claim 15  further comprising a first data warehouse server in communication with the first claim database server, the first data warehouse server comprising a data warehouse processor and a data warehouse memory;
 wherein the database processor is further configured to:
 receive a list of qualifying critical illnesses from the first data warehouse server; and 
 apply the list to the set of PA data to determine that the set of PA data indicates that the medical claim is associated with the qualifying critical illness. 
 
 
     
     
         17 . The trained predictive system of  claim 15 , wherein the processor is further configured to:
 identify a list of features for extraction; and   extract the component data, based on the list of features, from the set of PA data.   
     
     
         18 . The trained predictive system of  claim 15 , wherein the database processor is further configured to:
 identify a consulting review provider based on the set of PA data; and   transmit the request for the consulting review of the diagnosis and treatment plan to a computing device associated with the consulting review provider.   
     
     
         19 . The trained predictive system of  claim 15 , wherein the processor is further configured to:
 determine a likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan;   compare the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan against a predetermined threshold to evaluate inaccuracies in the diagnosis and treatment plan; and   on condition that the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan is greater than the predetermined threshold, determine that the medical claim is associated with the inaccurate diagnosis and treatment plan.   
     
     
         20 . The trained predictive system of  claim 15 , wherein the processor is further configured to:
 determine a likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan;   compare the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan against a predetermined threshold to evaluate inaccuracies in the diagnosis and treatment plan; and   on condition that the likelihood of whether the medical claim is associated with the inaccurate diagnosis and treatment plan is less than the predetermined threshold, generate a request that the medical claim be processed.